Mechanisms of Hierarchical Cortical Maturation

Examining litter specific variability in mice and its impact on neurodevelopmental studies

Our current understanding of litter variability in neurodevelopmental studies using mice may limit translation of neuroscientific findings. Higher variance of measures across litters than within, often termed intra-litter likeness, may be attributable to both pre- and postnatal environment. This study aimed to assess the litter-effect within behavioral assessments (2 timepoints) and anatomy using T1-weighted magnetic resonance images across 72 brain region volumes (4 timepoints) (36 C57bl/6J inbred mice; 7 litters: 19F/17M). Between-litter comparisons of brain and behavioral measures and their associations were evaluated using univariate and multivariate techniques. A power analysis using simulation methods was then performed on modeled neurodevelopment and to evaluate trade-offs between number-of-litters, number-of-mice-per-litter, and sample size. Our results show litter-specific developmental effects, from the adolescent period to adulthood for brain structure volumes and behaviors, and for their associations in adulthood. Our power simulation analysis suggests increasing the number-of-litters in experimental designs to achieve the smallest total sample size necessary for detecting different rates of change in specific brain regions. Our results demonstrate how litter-specific effects may influence development and that increasing the litters to the total sample size ratio should be strongly considered when designing neurodevelopmental studies.

NILRNN: A Neocortex-Inspired Locally Recurrent Neural Network for Unsupervised Feature Learning in Sequential Data

Unsupervised feature learning refers to the problem of learning useful feature extraction functions from unlabeled data. Despite the great success of deep learning networks in this task in recent years, both for static and for sequential data, these systems can in general still not compete with the high performance of our brain at learning to extract useful representations from its sensory input. We propose the Neocortex-Inspired Locally Recurrent Neural Network: a new neural network for unsupervised feature learning in sequential data that brings ideas from the structure and function of the neocortex to the well-established fields of machine learning and neural networks. By mimicking connection patterns in the feedforward circuits of the neocortex, our system tries to generalize some of the ideas behind the success of convolutional neural networks to types of data other than images. To evaluate the performance of our system at extracting useful features, we have trained different classifiers using those and other learnt features as input and we have compared the obtained accuracies. Our system has shown to outperform other shallow feature learning systems in this task, both in terms of the accuracies achieved and in terms of how fast the classification task is learnt. The results obtained confirm our system as a state-of-the-art shallow feature learning system for sequential data, and suggest that extending it to or integrating it into deep architectures may lead to new successful networks that are competent at dealing with complex sequential tasks.

Timely insertion of AMPA receptor in developing vestibular circuits is required for manifestation of righting reflexes and effective navigation

Vestibular information processed first by the brainstem vestibular nucleus (VN), and further by cerebellum and thalamus, underlies diverse brain function. These include the righting reflexes and spatial cognitive behaviour. While the cerebellar and thalamic circuits that decode vestibular information are known, the importance of VN neurons and the temporal requirements for their maturation that allow developmental consolidation of the aforementioned circuits remains unclear. We show that timely unsilencing of glutamatergic circuits in the VN by NMDA receptor-mediated insertion of AMPAR receptor type 1 (GluA1) subunits is critical for maturation of VN and successful consolidation of higher circuits that process vestibular information. Delayed unsilencing of NMDA receptor-only synapses of neonatal VN neurons permanently decreased their functional connectivity with inferior olive circuits. This was accompanied by delayed pruning of the inferior olive inputs to Purkinje cells and permanent reduction in their plasticity. These derangements led to deficits in associated vestibular righting reflexes and motor co-ordination during voluntary movement. Vestibular-dependent recruitment of thalamic neurons was similarly reduced, resulting in permanently decreased efficiency of spatial navigation. The findings thus show that well-choreographed maturation of the nascent vestibular circuitry is prerequisite for functional integration of vestibular signals into ascending pathways for diverse vestibular-related behaviours.

Modular strategy for development of the hierarchical visual network in mice

Hierarchical and parallel networks are fundamental structures of the mammalian brain^1-8. During development, lower- and higher-order thalamic nuclei and many cortical areas in the visual system form interareal connections and build hierarchical dorsal and ventral streams^9-13. One hypothesis for the development of visual network wiring involves a sequential strategy wherein neural connections are sequentially formed alongside hierarchical structures from lower to higher areas^14-17. However, this sequential strategy would be inefficient for building the entire visual network comprising numerous interareal connections. We show that neural pathways from the mouse retina to primary visual cortex (V1) or dorsal/ventral higher visual areas (HVAs) through lower- or higher-order thalamic nuclei form as parallel modules before corticocortical connections. Subsequently, corticocortical connections among V1 and HVAs emerge to combine these modules. Retina-derived activity propagating the initial parallel modules is necessary to establish retinotopic inter-module connections. Thus, the visual network develops in a modular manner involving initial establishment of parallel modules and their subsequent concatenation. Findings in this study raise the possibility that parallel modules from higher-order thalamic nuclei to HVAs act as templates for cortical ventral and dorsal streams and suggest that the brain has an efficient strategy for the development of a hierarchical network comprising numerous areas.

Normal development of the brain: a survey of joint structural-functional brain studies

Joint structural-functional (S-F) developmental studies present a novel approach to address the complex neuroscience questions on how the human brain works and how it matures. Joint S-F biomarkers have the inherent potential to model effectively the brain's maturation, fill the information gap in temporal brain atlases, and demonstrate how the brain's performance matures during the lifespan. This review presents the current state of knowledge on heterochronous and heterogeneous development of S-F links during the maturation period. The S-F relationship has been investigated in early-matured unimodal and prolonged-matured transmodal regions of the brain using a variety of structural and functional biomarkers and data acquisition modalities. Joint S-F unimodal studies have employed auditory and visual stimuli, while the main focus of joint S-F transmodal studies has been resting-state and cognitive experiments. However, nonsignificant associations between some structural and functional biomarkers and their maturation show that designing and developing effective S-F biomarkers is still a challenge in the field. Maturational characteristics of brain asymmetries have been poorly investigated by the joint S-F studies, and the results were partially inconsistent with previous nonjoint ones. The inherent complexity of the brain performance can be modeled using multifactorial and nonlinear techniques as promising methods to simulate the impact of age on S-F relations considering their analysis challenges.

Self-tuition as an essential design feature of the brain

We are curious by nature, particularly when young. Evolution has endowed our brain with an inbuilt obligation to educate itself. In this perspectives article, we posit that self-tuition is an evolved principle of vertebrate brain design that is reflected in its basic architecture and critical for its normal development. Self-tuition involves coordination between functionally distinct components of the brain, with one set of areas motivating exploration that leads to the experiences that train another set. We review key hypothalamic and telencephalic structures involved in this interplay, including their anatomical connections and placement within the segmental architecture of conserved forebrain circuits. We discuss the nature of educative behaviours motivated by the hypothalamus, innate stimulus biases, the relationship to survival in early life, and mechanisms by which telencephalic areas gradually accumulate knowledge. We argue that this aspect of brain function is of paramount importance for systems neuroscience, as it confers neural specialization and allows animals to attain far more sophisticated behaviours than would be possible through genetic mechanisms alone. Self-tuition is of particular importance in humans and other primates, whose large brains and complex social cognition rely critically on experience-based learning during a protracted childhood period.

This article is part of the theme issue ‘Systems neuroscience through the lens of evolutionary theory’.

Atypical Integration of Sensory-to-Transmodal Functional Systems Mediates Symptom Severity in Autism

A notable characteristic of autism spectrum disorder (ASD) is co-occurring deficits in low-level sensory processing and high-order social interaction. While there is evidence indicating detrimental cascading effects of sensory anomalies on the high-order cognitive functions in ASD, the exact pathological mechanism underlying their atypical functional interaction across the cortical hierarchy has not been systematically investigated. To address this gap, here we assessed the functional organisation of sensory and motor areas in ASD, and their relationship with subcortical and high-order trandmodal systems. In a resting-state fMRI data of 107 ASD and 113 neurotypical individuals, we applied advanced connectopic mapping to probe functional organization of primary sensory/motor areas, together with targeted seed-based intrinsic functional connectivity (iFC) analyses. In ASD, the connectopic mapping revealed topological anomalies (i.e., excessively more segregated iFC) in the motor and visual areas, the former of which patterns showed association with the symptom severity of restricted and repetitive behaviors. Moreover, the seed-based analysis found diverging patterns of ASD-related connectopathies: decreased iFCs within the sensory/motor areas but increased iFCs between sensory and subcortical structures. While decreased iFCs were also found within the higher-order functional systems, the overall proportion of this anomaly tends to increase along the level of cortical hierarchy, suggesting more dysconnectivity in the higher-order functional networks. Finally, we demonstrated that the association between low-level sensory/motor iFCs and clinical symptoms in ASD was mediated by the high-order transmodal systems, suggesting pathogenic functional interactions along the cortical hierarchy. Findings were largely replicated in the independent dataset. These results highlight that atypical integration of sensory-to-high-order systems contributes to the complex ASD symptomatology.

Breakdown of Whole-brain Dynamics in Preterm-born Children

The brain operates at a critical point that is balanced between order and disorder. Even during rest, unstable periods of random behavior are interspersed with stable periods of balanced activity patterns that support optimal information processing. Being born preterm may cause deviations from this normal pattern of development. We compared 33 extremely preterm (EPT) children born at < 27 weeks of gestation and 28 full-term controls. Two approaches were adopted in both groups, when they were 10 years of age, using structural and functional brain magnetic resonance imaging data. The first was using a novel intrinsic ignition analysis to study the ability of the areas of the brain to propagate neural activity. The second was a whole-brain Hopf model, to define the level of stability, desynchronization, or criticality of the brain. EPT-born children exhibited fewer intrinsic ignition events than controls; nodes were related to less sophisticated aspects of cognitive control, and there was a different hierarchy pattern in the propagation of information and suboptimal synchronicity and criticality. The largest differences were found in brain nodes belonging to the rich-club architecture. These results provide important insights into the neural substrates underlying brain reorganization and neurodevelopmental impairments related to prematurity.

Developmental Changes in Pyramidal Cell Morphology in Multiple Visual Cortical Areas Using Cluster Analysis

Neuronal morphology is characterized by salient features such as complex axonal and dendritic arbors. In the mammalian brain, variations in dendritic morphology among cell classes, brain regions, and animal species are thought to underlie known differences in neuronal function. In this work, we obtained a large dataset from http://neuromorpho.org/ comprising layer III pyramidal cells in different cortical areas of the ventral visual pathway (V1, V2, V4, TEO, and TE) of the macaque monkey at different developmental stages. We performed an in depth quantitative analysis of pyramidal cell morphology throughout development in an effort to determine which aspects mature early in development and which features require a protracted period of maturation. We were also interested in establishing if developmental changes in morphological features occur simultaneously or hierarchically in multiple visual cortical areas. We addressed these questions by performing principal component analysis (PCA) and hierarchical clustering analysis on relevant morphological features. Our analysis indicates that the maturation of pyramidal cell morphology is largely based on early development of topological features in most visual cortical areas. Moreover, the maturation of pyramidal cell morphology in V1, V2, V4, TEO, and TE is characterized by unique developmental trajectories.

Wiring of higher-order cortical areas: Spatiotemporal development of cortical hierarchy

A hierarchical development of cortical areas was suggested over a century ago, but the diversity and complexity of cortical hierarchy properties have so far prevented a formal demonstration. The aim of this review is to clarify the similarities and differences in the developmental processes underlying cortical development of primary and higher-order areas. We start by recapitulating the historical and recent advances underlying the biological principle of cortical hierarchy in adults. We then revisit the arguments for a hierarchical maturation of cortical areas, and further integrate the principles of cortical areas specification during embryonic and postnatal development. We highlight how the dramatic expansion in cortical size might have contributed to the increased number of association areas sustaining cognitive complexification in evolution. Finally, we summarize the recent observations of an alteration of cortical hierarchy in neuropsychiatric disorders and discuss their potential developmental origins.

Differences between the child and adult brain in the local functional structure of the cerebral cortex

Imaging studies on neuronal network formation provide relevant information as to how the brain matures during adolescence. We used a novel imaging approach combining well-established MRI measures of local functional connectivity that jointly provide qualitatively different information relating to the functional structure of the cerebral cortex. To investigate the adolescent transition into adulthood, we comparatively assessed 169 preadolescents aged 8-12 years and 121 healthy adults. Whole-brain functional connectivity maps were generated using multi-distance measures of intracortical neural activity coupling defined within iso-distant local areas. Such Iso-Distant Average Correlation (IDAC) measures therefore represent the average temporal correlation of a given brain unit, or voxel, with other units situated at increasingly separated iso-distant intervals. The results indicated that between-group differences in the functional structure of the cerebral cortex are extensive and implicate part of the lateral prefrontal cortex, a medial frontal/anterior cingulate region, the superior parietal lobe extending to the somatosensory strip and posterior cingulate cortex, and local connections within the visual cortex, hippocampus, amygdala and insula. We thus provided detail of the cerebral cortex functional structure maturation during the transition to adulthood, which may serve to establish more accurate links between adolescent performance gains and cerebral cortex maturation. Remarkably, our study provides new information as to the cortical maturation processes in prefrontal areas relevant to executive functioning and rational learning, medial frontal areas playing an active role in the cognitive appraisal of emotion and anxiety, and superior parietal cortices strongly associated with bodily self-consciousness in the context of body image formation.

The early overgrowth theory of autism spectrum disorder: Insight into convergent mechanisms from valproic acid exposure and translational models

The development of new approaches for the clinical management of autism spectrum disorder (ASD) can only be realized through a better understanding of the neurobiological changes associated with ASD. One strategy for gaining deeper insight into the neurobiological mechanisms associated with ASD is to identify converging pathogenic processes associated with human idiopathic clinicopathology that are conserved in translational models of ASD. In this chapter, we first present the early overgrowth theory of ASD. Second, we introduce valproic acid (VPA), one of the most robust and well-known environmental risk factors associated with ASD, and we summarize the rapidly growing body of animal research literature using VPA as an ASD translational model. Lastly, we will detail the mechanisms of action of VPA and its impact on functional neural systems, as well as discuss future research directions that could have a lasting impact on the field.

A systematic review of neurological impairments in myalgic encephalomyelitis/ chronic fatigue syndrome using neuroimaging techniques

BACKGROUND

Myalgic encephalomyelitis/ Chronic Fatigue Syndrome (ME/CFS) is a multi-system illness characterised by a diverse range of debilitating symptoms including autonomic and cognitive dysfunction. The pathomechanism remains elusive, however, neurological and cognitive aberrations are consistently described. This systematic review is the first to collect and appraise the literature related to the structural and functional neurological changes in ME/CFS patients as measured by neuroimaging techniques and to investigate how these changes may influence onset, symptom presentation and severity of the illness.

METHODS

A systematic search of databases Pubmed, Embase, MEDLINE (via EBSCOhost) and Web of Science (via Clarivate Analytics) was performed for articles dating between December 1994 and August 2019. Included publications report on neurological differences in ME/CFS patients compared with healthy controls identified using neuroimaging techniques such as magnetic resonance imaging, positron emission tomography and electroencephalography. Article selection was further refined based on specific inclusion and exclusion criteria. A quality assessment of included publications was completed using the Joanna Briggs Institute checklist.

RESULTS

A total of 55 studies were included in this review. All papers assessed neurological or cognitive differences in adult ME/CFS patients compared with healthy controls using neuroimaging techniques. The outcomes from the articles include changes in gray and white matter volumes, cerebral blood flow, brain structure, sleep, EEG activity, functional connectivity and cognitive function. Secondary measures including symptom severity were also reported in most studies.

CONCLUSIONS

The results suggest widespread disruption of the autonomic nervous system network including morphological changes, white matter abnormalities and aberrations in functional connectivity. However, these findings are not consistent across studies and the origins of these anomalies remain unknown. Future studies are required confirm the potential neurological contribution to the pathology of ME/CFS.

The unique expression profile of FAM19A1 in the mouse brain and its association with hyperactivity, long-term memory and fear acquisition

Neurodevelopment and mature brain function are spatiotemporally regulated by various cytokines and chemokines. The chemokine-like neuropeptide FAM19A1 is a member of family with sequence similarity 19 (FAM19), which is predominantly expressed in the brain. Its highly conserved amino acid sequence among vertebrates suggests that FAM19A1 may play important physiological roles in neurodevelopment and brain function. Here we used a LacZ reporter gene system to map the expression pattern of the FAM19A1 gene in the mouse brain. The FAM19A1 expression was observed in several brain regions starting during embryonic brain development. As the brain matured, the FAM19A1 expression was detected in the pyramidal cells of cortical layers 2/3 and 5 and in several limbic areas, including the hippocampus and the amygdala. FAM19A1-deficient mice were used to evaluate the physiological contribution of FAM19A1 to various brain functions. In behavior analysis, FAM19A1-deficient mice exhibited several abnormal behaviors, including hyperactive locomotor behavior, long-term memory deficits and fear acquisition failure. These findings provide insight into the potential contributions of FAM19A1 to neurodevelopment and mature brain function.

Ocular Dominance Plasticity of Areas 17 and 21a in the Cat

The visual system is organized in a parallel and hierarchical architecture. However, the plasticity in hierarchical neural networks is controversial across different response features and at different levels. In this study, we recorded areas 17 and 21a, earlier and intermediate stages of the visual cortex in the cat, respectively, by single-unit recording and intrinsic-signal optical imaging. We found that ocular dominance (OD) plasticity evoked by monocular deprivation (MD) was stronger in area 21a than in area 17 in the critical period (CP), and this plasticity became weaker but still persisted in area 21a while it disappeared in area 17 beyond the CP. These results suggest a diversified functional plasticity along the visual information processing pathways in a hierarchical neural network.

Multimodal gradients across mouse cortex

The primate cerebral cortex displays a hierarchy that extends from primary sensorimotor to association areas, supporting increasingly integrated function underpinned by a gradient of heterogeneity in the brain's microcircuits. The extent to which these hierarchical gradients are unique to primate or may reflect a conserved mammalian principle of brain organization remains unknown. Here we report the topographic similarity of large-scale gradients in cytoarchitecture, gene expression, interneuron cell densities, and long-range axonal connectivity, which vary from primary sensory to prefrontal areas of mouse cortex, highlighting an underappreciated spatial dimension of mouse cortical specialization. Using the T1-weighted:T2-weighted (T1w:T2w) magnetic resonance imaging map as a common spatial reference for comparison across species, we report interspecies agreement in a range of large-scale cortical gradients, including a significant correspondence between gene transcriptional maps in mouse cortex with their human orthologs in human cortex, as well as notable interspecies differences. Our results support the view of systematic structural variation across cortical areas as a core organizational principle that may underlie hierarchical specialization in mammalian brains.

Gradients of connectivity distance in the cerebral cortex of the macaque monkey

Cortical connectivity conforms to a series of organizing principles that are common across species. Spatial proximity, similar cortical type, and similar connectional profile all constitute factors for determining the connectivity between cortical regions. We previously demonstrated another principle of connectivity that is closely related to the spatial layout of the cerebral cortex. Using functional connectivity from resting-state fMRI in the human cortex, we found that the further a region is located from primary cortex, the more distant are its functional connections with the other areas of the cortex. However, it remains unknown whether this relationship between cortical layout and connectivity extends to other primate species. Here, we investigated this relationship using both resting-state functional connectivity as well as gold-standard tract-tracing connectivity in the macaque monkey cortex. For both measures of connectivity, we found a gradient of connectivity distance extending between primary and frontoparietal regions. In the human cortex, the further a region is located from primary areas, the stronger its connections to distant portions of the cortex, with connectivity distance highest in frontal and parietal regions. The similarity between the human and macaque findings provides evidence for a phylogenetically conserved relationship between the spatial layout of cortical areas and connectivity.